How Big Data can resolve K-12’s most fundamental challenges.

GUEST COLUMN | by Joel Sackett

Efforts to improve student achievement in the U.S. have skyrocketed over the years. Despite these efforts, several issues continually thwart America’s progress towards higher levels of achievement. Fortunately, the education landscape is evolving, and concepts such as big data and predictive analytics will undeniably move the dial forward. Below, we discuss several systemic issues and highlight ways in which data-driven decision making can address them.

1. Kids Are Falling Through the Cracks

When examining educational achievement, the disparity between the richest and poorest children is clear, and in fact, has worsened over the years. 9% of the lowest income quartile receives a college diploma, compared to 75% of the highest income quartile. With personnel and school resources being stretched thin in poorer districts, kids inevitably fall through the cracks. Data can serve as vital indicators to help address such issues, and as data analysis technologies become affordable, its impact will be more widespread:

•       At-risk data modeling: Interventions to address student dropouts are often implemented too late. Thankfully, data modeling can further improve educators’ abilities to detect at-risk students early on by identifying those who are statistically likely to drop out based on factors such as students’ course grades, attendance, and socioeconomic data. This enables educators to implement intervention programs earlier, allowing for more time for retention initiatives.
•       Longitudinal student data tracking: Maintaining an alumni feedback loop is becoming critical for districts to monitor college retention and graduation rates, and to assess how effective their college- and career- readiness programs are. Longitudinal student data tracking serves as the connector between high schools and colleges, allowing districts to keep a pulse on their students. We see increased data collaboration to address this issue, with state and local education departments developing centralized tracking data systems. Innovators are also taking charge; Founder Alexandra Bernadotte, for instance, is achieving her mission to improve student retention and graduation rates through Beyond 12, a non-profit organization that offers a robust technology-based alumni tracking platform and coaching services for students.

2. Teachers Aren’t Effective Enough

Teacher quality, and its impact on student achievement, is very much front and center on the American education reform platform, particularly as U.S. students continue to perform below other countries in international exams. To elevate student performance, the U.S. needs to improve education and training to increase the supply of teacher talent; districts need to better identify and hire the best from the talent pool; and customized professional development and incentives need to be instituted to further nurture teachers. All of those areas require a hands-on-approach; where data can help is in the form of predictive analytics. Research shows that certain teacher qualifications and career experiences are statistically correlated to student achievement gains; through predictive analytics, even before the hiring decision, districts could better predict how likely a teacher candidate is to positively impact student achievement. Approximately 14% of corporate human resources organizations currently use advanced or predictive analytics to make decisions about hiring, promotions or compensation; we expect similar trends in K-12 to take hold in the coming years.

3. K-12 Budgets Are Shrinking

According to the Center on Budget and Policy Priorities, the majority of state school systems have cut spending since 2008. Districts are being pressured to do more with less, creating the gradual shift we are seeing of districts thinking and acting more like businesses. A key initiative, especially in districts facing challenging financial situations, is a focus on operational efficiency. Several years ago San Diego Unified School District’s budget was reduced by 25% despite rising enrollment; in response, by analyzing its attendance, procurement, and operational data using Oracle Exalytics, the district was able to reap $4.4 million in savings. At Hanover Research, an education research firm, 20% of projects requested by districts in 2013 consisted of data analysis and best practices research focused on ways to improve operational efficiency. These types of project requests are expected to increase as budgets remain lean.

4. Kids Need Personalized Learning

Students learn at different paces, but with the traditional U.S. educational model, they have few, if any, customized learning options available to them in the classroom. While the shift from teacher- and curriculum-centered learning to student-centered learning has long been underway in the U.S., digital technology can now assist this movement in new ways by using response data to learn and adjust to the student’s needs. We are seeing both the big players, such as Pearson and Scholastic, along with startups, such as  Knowre, create a rich new market of adaptive learning tools, which allow schools to manage and differentiate instruction to have a positive impact on student achievement. Edtech companies are rapidly launching adaptive learning tools; these tools, combined with project-based learning and custom-career pathways, are all best practice solutions to developing personalized learning environments, a major key to improving student achievement.

Why EdTech Makes Big Data Approachable

The issues discussed above are complex, and traditionally would have required either a team of skilled analysts or would have been impossible to accomplish due to the complexity of the data set. Thankfully, with edtech, districts enjoy the simplification of complexity, with technologies doing most of the analytical work and providing users with simple, understandable and quick results. With mounting competition in the K-12 market, edtech companies are realizing the need for extra value in the form of rich customer service, aimed to ensure seamless technology integration and an ongoing feedback loop that results in continued enhancements. As districts continue to embrace data-driven decision making, we will take one major step forward towards improving student achievement.

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Joel Sackett is the Product Manager for Paragon K12, a K-12 software solution by Hanover Research, a global information services firm providing knowledge support to both for-profit and non-profit organizations. Paragon K12 is a teacher selection tool that uses predictive analytics to enable hiring managers to assess teacher candidates most likely to positively impact student achievement. Write to: jsackett@hanoverresearch.com or follow Paragon K12 and Hanover Research K12 on Twitter.